# coding:utf-8
from keras_applications.inception_v3 import InceptionV3
import keras
from keras.layers import Conv2D, MaxPooling2D, Input
# inception模型的trick是将大卷积核变成小卷积核，
# 将多个卷积核的运算结果进行连接，充分利用多尺度信息
input_image = Input(shape=(256,256,3))

tower_1 = Conv2D(64,(1,1),padding='same',activation='relu')(input_image)
tower_1 = Conv2D(64,(3,3),padding='same',activation='relu')(tower_1)

tower_2 = Conv2D(64,(1,1),padding='same',activation='relu')(input_image)
tower_2 = Conv2D(64,(5,5),padding='same',activation='relu')(tower_2)

tower_3 = MaxPooling2D((3,3),padding='same',strides=(1,1))(input_image)
tower_3 = Conv2D(64,(1,1),padding='same',activation='relu')(tower_3)

output = keras.layers.concatenate([tower_1,tower_2,tower_3],axis=1)


